• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.129-155
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• 2008

The rate of antibiotics prescription for an acute airway infection significantly varies depending upon the diagnosis type, specialty, and the location of the hospital along with many other related factors. The objective of this study is to empirically investigate the possible relationship between the antibiotics prescription rates for an acute airway infection and the degree of competition in the hospital market regions of mainly the providers of primary medical care services such as clinics, internal medicines, pediatrics and otorhinolaryngology department. Using the data from Health Insurance Review and Assessment Service (HIRA) regarding the hospitals' antibiotics prescription rates for the acute airway infection and controlling for selected variables of demand and supply sectors, this study tries to figure out that the degree of competition in the hospital market, regardless of what type of competition indexes we employed, has a statistically significant effect on the variations of antibiotics prescription rate of the clinics in local areas. This result implies that as an economic consideration itself, the change in the degree of competition in the hospital market can play a crucial role influencing the treatment behaviors of the medical doctors. More specifically, this study reveals that as the degree of competition increases the antibiotics prescription rate goes up. This result means that if the market becomes more competitive in a specific region so that it might cause a reduction in doctor's income, doctors with rational decision-making process, recognize that the benefit created from inducing patients' seemingly unnecessary demand for medical care (income effect) would be higher than the costs associated with sustaining their targeted income (substitution effect). It is because that the doctors are more likely to prescribe antibiotics which create relatively higher margins than other medical care services in order to sustain their targeted income when the hospital market competition becomes tighter. Even though this study empirically confirms that antibiotics prescription can be affected by the economic incentives, it still raises following issues as limitations of the study: first issue is about the representativeness of the hospital regions segregated for this study, which might be weak in explaining whether these regions are mutually exclusive in reality. Patients actually consider the quality of services, transportation cost, time costs, and any other related factors choosing the doctors or hospitals, and in that sense, this study rules out 'border-crossing' in using the medical care services. Second issue arises in capturing the data of antibiotics prescription rate. Since we use the average rate for each medical institution, we cannot figure out the average rate for each patient so that we are not able to control for the variation of patients' medical conditions. It is because of the unavailability of data regarding each patient's medical condition from HIRA. Thirdly, since this study mainly analyzes the medical institutions providing primary care such as clinics, internal medicines, pediatrics, and otorhinolaryngology department, it is skeptical of whether those institutions can represent the hospital market in respective regions and truly reflect the degree of competition. It needs to extend the study areas and disease types as well as any micro data for future studies.

• The Korean Journal of Community Living Science
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• v.16 no.4
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• pp.83-93
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• 2005

This study was conducted to provide information about the behavioral intentions to diet in adolescent females. To explain the behavior intention to diet, a conceptual framework based on the ' Social Support, Control and the Stress Process Model ' and the ' Theory of Reasoned Actio ' was used. The survey was carried out by self-questionnaires with 463 female high school and college students in Daegu. Analysis of data was done by using mean, correlation and multiple regression analysis with the SAS computer program. Subjects were divided into 3 groups-underweight, normal weight, and overweight-according to their current body size. The most powerful influencing factor related to perceived stress -that is dissatisfaction with body image- was the current figure, regardless of current body size. The fatter the current body size, the higher the score for the behavioral intention to diet. In attitude toward the behavior of dieting, the fatter the current figure, the higher the attitude score, and the belief of behavioral outcome was the main decision variable. For the score of the subjective norm, the overweight group was significantly higher than other groups. The influencing factors for the behavioral intention to diet were perceived stress and attitude toward dieting behavior, especially beliefs of behavioral outcome.

• 대한공업교육학회지
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• v.41 no.1
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• pp.68-87
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• 2016

This research conducted a survey for total 166 teachers of schools so as to analyze validity and satisfaction for performance objectives of SMB administration subsidy the HRDP and the CEP in Specialized High School. The results of research are as follows. First, teachers recognize that purpose of HRDP is to expand employment of specialized high school and provide human resource of SMB. And, they recognize that HRDP is important to improve school outcomes and makes a positive effect on the improvement of school outcomes. Second, teachers recognize that objectives of HRDP are improvement of student's understanding for SMB, improvement of teacher's understanding for SMB, improvement of SMB's understanding of school, cultivation of student's occupational view, systematization of career guiding program based on employment process, strengthening of industry-academia cooperation education, improvement of the level of student's skill, fulfillment of workplace experience and practice focusing workplace learning, training of customized human resource for SMB, improvement of student's adaptation to the workplace, improvement of employment rate for SMB, expansion of job opportunities for students with SMB, preparation of the base of connection between school and SMB, publicity of school, expansion of opportunities to cooperate between SMB and school, establishment of cooperative system among industrial association and school, introduction and operation of the employment connective model for joint education and employment, strengthening of field professionalism of teachers. However, satisfaction for the achievement of objectives of HRDP except for strengthening of industry-academia cooperation education and improvement of employment rate for SMB is relatively lower than the validity. Third, teachers in charge of human resource training business of middle and small sized company's specialized high school recognize that objectives of CEP are expansion of job opportunities for students with SMB, excavation of good-quality SMB, expansion of opportunities to cooperate between SMB and school, fulfillment of workplace learning, improvement of student's major foundation and in-depth skill, improvement of literacy, math, teamwork and communication abilities for students' job performance, improvement of student's working attitude and student's proper career exploration decision. However, satisfaction for achievement of objectives of CEP is relatively lower than the validity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.6
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• pp.1634-1647
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• 2007

"To invest or not to invest?" Most business leaders are frequently faced with this question on new and ongoing projects. The challenge lies in deciding what projects to choose, expand, contract, defer, or abandon. The project valuation tools used in this process are vital to making the right decisions. Traditional tools such as discounted cash flow (DCF)/net present value (NPV) assume a "fixed" path ahead, but real world projects face uncertainties, forcing us to change the path often. Comparing to other traditional valuation methods, the real options approach captures the flexibility inherent to investment decisions. The use of real options has gained wide acceptance among practitioners in a number of several industries during the last few decades. Even though the options are present in all types of business decisions, it is still not considered as a proper method of valuation in some industries. Mining has been comparably slow to adopt new valuation techniques over the years. The reason fur this is not entirely clear. One possible reason is the level and types of risks in mining. Not only are these risks high, but they are also more numerous and involve natural risks compared with other industries. That is why the purpose of this study is to deal with a more practical approach to project valuation, known as real options analysis in mining industry. This paper provides a case study approach to the copper mining industry using a real options analysis. It shows how companies can minimize investment risks, exercise flexibility in decision making and maximize returns.

• Journal of the Korean association of regional geographers
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• v.3 no.1
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• pp.183-198
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• 1997

This case study was conducted by verification the site characteristics based on the questionnaire and interview obtained from the all factories located at No. 1 developing area in Kumi industrial complex. The site characteristics were presumed from the process of location behavior and spatial linkage. Kumi industrial complex was developed to improve export industry at national levels by providing chief land price and benefiting various tax. Kumi industrial complex which enticed many factories is playing an important role in export industry in Korea. At beginning, the detention of large enterprises promoted the establishment of related small to medium sized factories into the complex. Two distinctive industries. textile and electronic, were reflected by the purpose to establish the complex and industrial characteristics of Taegu city. respectively. In Kumi industrial complex, positive responses on traffic and raw material supply and negative reactions on the environmental impact on social community as well as high labor charge were investigated. Especially the higher labor cost prevented to hire laborers effectively. In the linkages of spatial and raw material, most factories in the complex depended on the availability of out side the Kumi city. For the textile factories, the supply of raw material and parts were relied on Taegu and/or other cities, whereas in electronic factories purchased them mainly from other cities and partly from abroad. Although questionnaire and interview suggested it, most of the parts were supplied by a parts maturing companies on the complex to a few large enterprises. In the marketing linkage, textile factories revealed higher relation-ship with the foreign countries and sewing factories in Korea. On the other hand, electronic factories have strong relation-ships in the marketing linkage to the parts supplying companies in the complex or large-scale resembling companies in other cities. In the textile companies, the right for decision on purchasing raw materials and parts is belonging to the owner whereas mother enterprise usually have the right for the marketing. In the case of the electronic factories, all the purchasing activities are related to the sub-contracting companies. In the service linkage, the Quality of the service created spatial distinction. There was high linkages on inside of Kumi complex for the low grade services such as repairing and installing machines, whereas strong linkages on outside of the complex for the high grade services such as management, law, taxation, new product development. and manufacturing technology. In the linkages of activity on the R&D (research and development), electronic factories do not have sufficiently qualified institutes in the complex. Strong regional linkages in the field of textile and electronic industries revealed limitations of the local industrial complex. In the sub-contracting linkage, high linkage ship within Kumi boundary reflected the characteristics of industrial site in the complex. There, most decisions by the companies centered by the mother enterprise.

• Journal of the Korean association of regional geographers
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• v.20 no.2
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• pp.163-175
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• 2014

This study is to explain social capital characteristics of Filipino immigrant women at the level of neighborhood. This research targeted Filipino immigrant women in the metropolis, small town and rural area in Korea to find out the relevance of individual property and characteristics of the community and social capital of neighboring communities- school community, cathedral community, etc- through measurement of the participants' recognition. This study reveals that differences exist in the relationship between length of residence and social capital in the school community and the catholic church community. There is a significant positive relationship between length of residence and political factors in the catholic church community, thereby having a better relationship with longer period of stay, while length of residence and confidence show a negative trend in the school community, leading to less confidence. The catholic church community holds a dominant position in homogeneity, cohesion, and the amount of social capital. According to the findings, social capital 'relation' is more closely related to homogeneity of the community, 'norms' to cohesion. 'Relation and norms' and 'confidence and politics' factors are recognized similarly in both communities, thus resulting in the recognition that decision making within the community, the share of value, and observance of social norms approximate a friendly relationship among members, and satisfaction level, emotional support, and confidence among members approach politics that members can talk about their personal matters. It is noted in the research process that the symbolism of the cathedral community as a transnational circuit behavior occurs where collective culture and personal desires of Filipino immigrant women were combined with production of social capital. Filipino immigrant women's awareness of community and social capital appearing in the cathedral community show that not only residence, along with the cultural identity of Filipino immigrant women, but also collective social and cultural characteristics, such as 'family reunion' can not be overlooked. In particular, at this time when discussion and debate on the interculturalism over multiculturalism is heating up, communal spirit and social capital based on the ethnic identity are important in that they can be a crucial path to the cross-cultural interaction with our society, therefore, a study on the social capital of the ethnic community needs to be encouraged and extended to more diverse communities, to the space of the multilayered scale.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.617-628
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• 2022

A ground support pattern should be designed by properly integrating various support materials in accordance with the rock mass grade when constructing a tunnel, and a technical decision must be made in this process by professionals with vast construction experiences. However, designing supports at the early stage of tunnel design, such as feasibility study or basic design, may be very challenging due to the short timeline, insufficient budget, and deficiency of field data. Meanwhile, the design of the support pattern can be performed more quickly and reliably by utilizing the machine learning technique and the accumulated design data with the rapid increase in tunnel construction in South Korea. Therefore, in this study, the design data and ground exploration data of 48 road tunnels in South Korea were inspected, and data about 19 items, including eight input items (rock type, resistivity, depth, tunnel length, safety index by tunnel length, safety index by rick index, tunnel type, tunnel area) and 11 output items (rock mass grade, two items for shotcrete, three items for rock bolt, three items for steel support, two items for concrete lining), were collected to automatically determine the rock mass class and the support pattern. Three machine learning models (S1, A1, A2) were developed using two machine learning algorithms (SVR, ANN) and organized data. As a result, the A2 model, which applied different loss functions according to the output data format, showed the best performance. This study confirms the potential of support pattern design using machine learning, and it is expected that it will be able to improve the design model by continuously using the model in the actual design, compensating for its shortcomings, and improving its usability.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1361-1371
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• 2021

Among smart city services, the crime and disaster prevention sector accounted for the highest 24% in 2018. The most important platform for providing real-time situation information is CCTV (Closed-Circuit Television). Therefore, it is essential to create the actual CCTV surveillance coverage to maximize the usability of CCTV. However, the amount of CCTV installed in Korea exceeds one million units, including those operated by the local government, and manual identification of CCTV coverage is a time-consuming and inefficient process. This study proposed a method to efficiently construct CCTV's actual surveillance coverage and reduce the time required for the decision-maker to manage the situation. For this purpose, first, the exterior orientation parameters and focal lengths of the pre-installed CCTV cameras, which are difficult to access, were calculated using the point cloud data of the MMS (Mobile Mapping System), and the FOV (Field of View) was calculated accordingly. Second, using the FOV result calculated in the first step, CCTV's actual surveillance coverage area was constructed with 1 m, 2 m, 3 m, 5 m, and 10 m grid interval considering the occluded regions caused by the buildings. As a result of applying our approach to 5 CCTV images located in Uljin-gun, Gyeongsnagbuk-do the average re-projection error was about 9.31 pixels. The coordinate difference between calculated CCTV and location obtained from MMS was about 1.688 m on average. When the grid length was 3 m, the surveillance coverage calculated through our research matched the actual surveillance obtained from visual inspection with a minimum of 70.21% to a maximum of 93.82%.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.